A digital image is a representation of a two-dimensional analog image as a finite set of pixels. Digital images can be created by a variety of devices, such as digital cameras, scanners, and various other computing and imaging devices. Digital image processing is the use of computer algorithms to perform image processing on digital images. Image processing operations include, for example, color to gray-scale conversion, color adjustment, intensity adjustment, scene analysis, object recognition, and resolution adjustment.
Resolution adjustment is typically accomplished using a spatial interpolation method. Spatial interpolation refers to the process of changing the spatial resolution of a digital image. Spatial interpolation can either result in the compression of a digital image by removing pixels from the digital image, or in the enlargement of a digital image by adding pixels to the digital image. Digital images can be compressed in order to reduce the memory required to store and/or transmit a digital image, for example. Digital images can be enlarged in order to overcome the limitations in optical capabilities of a digital camera by increasing the number of pixels representing a visual scene, for example.
Conventional methods for enlarging a digital image include bilinear and bicubic interpolation. However, both of these approaches present problems. For example, when bilinear interpolation is used to enlarge a digital image, the process can result in a relatively low quality image. Alternatively, the use of a bicubic interpolation process, which may result in a higher quality image, can be relatively computationally inefficient and therefore costly in terms of time and processing resources. Thus, it would be an advancement in the art to provide an improved image processing technique for enlarging digital images having high image quality and that does so in a manner that is computationally efficient.